An Image Classification Model trained on 6000+ images of various plants. When an image is uploaded, it returns whether the plant is poisonous or not. Tri-Valley Hacks 2023 project.

The aim is to build a predictive model that can accurately classify whether the employee is likely to leave or the employee is likely to stay in the company. This allows companies to take proactive measures, such as improving working conditions, offering promotions, or addressing dissatisfaction, to retain valuable employees.

Machine Learning Model for Leaf Disease Detection

LyriGenesis is an Introduction to Artificial Intelligence (AI) Final Project. This is an AI model that takes a word or phrase from a user and uses it to generate song lyrics whose length is also based on another input by the user.

Machine Learning Model for Predicting Personality Traits

This Machine Learning Model Predict behavior to retain customers in a Telecommunication Company. The focus of the project is on customer retention.

This Machine Learning Model Predict behavior to retain customers of a credit card services.

Repository which consists different code snippets and projects for my personal lessons recorded at the University of San Francisco in during learning of the Machine Learning.

ЭМИИА | EMIIA | КОГНИТИВНАЯ РАДИООПТИКА | COGNITIVE RADIO OPTICS | РАДИООПТИКА | RADIO OPTICS

Deep learning model and code for Toxic Comments Classification Challenge on Kaggle. Simple framework for similar competitions.

A method for predicting NAG interacting residues in a protein from its primary sequence

Assists in the creation of convolutional neural network models for image classification. Models are generated with the Keras library, wrapped from Python in C# to allow use between languages.

Building an ML model for detecting if a patient is COVID-19 positive or not. Based on dataset: https://www.kaggle.com/datasets/andyczhao/covidx-cxr2

📊 [ML] Classification Problem Solution: Guessing the type of a corrupted file

The credit card fraud detection model employs a Random Forest Classifier, a robust ensemble learning technique. It analyzes various transaction features to accurately identify fraudulent activities, leveraging the collective decision-making of multiple decision trees to enhance detection accuracy and resilience against data imbalances.

Machine Learning Model for Star Classification

Pipeline Classifier of Messages

Plasma cell-free DNA hydroxymethylomes discriminate disease state in EGFR-mutant non-small cell lung cancer.

Diabetes Prediction using Machine Learning

This is a Supervised Learning Model which predicts the Price of Real Estate in Madrid, Spain.